Quality of Service in Wireless Sensor Networks: A Survey and Related Patents

Balen, Josip; Žagar, Drago; Martinović, Goran

doi:10.2174/1874479611104030188

Cited by 14 publications

(9 citation statements)

References 36 publications

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“…Guaranteeing QoS for the numerous types of data is an important goal in network [1,[30][31][32]. Recently, researches are focusing on dynamic QoS mechanism as different data types require different QoS requirements [33,34].…”

Section: Qos Provisioning Methodsmentioning

confidence: 99%

Software‐defined dynamic QoS provisioning for smart metering in energy Internet using fog computing and network calculus

Huang

Liu

et al. 2018

IET cyber-phys. syst.

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Section: Qos Provisioning Methodsmentioning

confidence: 99%

Software‐defined dynamic QoS provisioning for smart metering in energy Internet using fog computing and network calculus

Huang

Liu

et al. 2018

IET cyber-phys. syst.

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“…One of the challenges in CBSN is to send data reliably, with the lowest delay, highest throughput and energy efficiency, in a network where not only nodes placed on one body change location as the person moves, but also different bodies move in different directions, creating unpredictable mobility patterns and leading to highly dynamic network topology. • High scalability requirements [16]. Unlike single BSN, the number of nodes in CBSN is not limited and can reach thousands of devices, as more bodies, each holding many sensors, can join the network.…”

Section: Major Challenges In Cbsnmentioning

confidence: 99%

“…Sensors in CBSN have limited power; therefore energy constraints should be always kept in mind when choosing MAC protocols, routing and localization algorithms, security systems, etc. • Heterogeneous traffic and irregular traffic pattern [16].…”

Section: Major Challenges In Cbsnmentioning

confidence: 99%

Collaborative body sensor networks: Taxonomy and open challenges

Boudargham

Abdo

Demerjian

et al. 2018

2018 IEEE Middle East and North Africa Communications Conference (MENACOMM)

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Single Body Sensor Networks (BSNs) have gained a lot of interest during the past few years. However, the need to monitor the activity of many individuals to assess the group status and take action accordingly has created a new research domain called Collaborative Body Sensor Network (CBSN). In such a new field, understanding CBSN's concept and challenges over the roots requires investigation to allow the development of suitable algorithms and protocols. Although there are many research studies in BSN, CBSN is still in its early phases and studies around it are very few. In this paper, we define and taxonomize CBSN, describe its architecture, and discuss its applications. The differences between CBSN and other sensor networks are highlighted to justify the need to develop new protocols and schemes appropriate for this type of networks. The major challenges are discussed, and open research issues are outlined to help in identifying new research directions in CBSN. To the best of our knowledge, this article is the first to define CBSN as a standalone domain that is distinct from other sensor networks and to develop its taxonomy.

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“…Wireless sensors can be used in locations that are difficult to access due to extreme conditions such as high temperature, humidity, and pressure [2]. Also, they can be used to form a WSN that would allow technicians to monitor a large number of different locations far from their position, such as tracking targets in a battlefield and monitoring the physical environment for the benefit of agriculture and plants [3]. Every sensor node is capable of communicating with other sensor nodes wirelessly and monitoring an environment.…”

Section: Introductionmentioning

confidence: 99%

Use of multiple mobile sinks in wireless sensor networks for large‐scale areas

Al-Behadili¹,

Alwane²,

Al‐Yasir

et al. 2020

IET wirel. sens. syst.

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Sensing coverage and network connectivity are two of the most fundamental issues to ensure that there are effective environmental sensing and robust data communication in a wireless sensor network (WSN) application. Random positioning of nodes in a WSN may result in random connectivity, which can cause a large variety of key parameters within the WSN. For example, data latency and battery lifetime can lead to the isolation of nodes, which causes a disconnection between nodes within the network. These problems can be avoided by using mobile data sinks, which travel between nodes that have connection problems. This research aims to design, test, and optimise a data collection system that addresses the isolated node problem, as well as to improve the connectivity between sensor nodes and base station, and to reduce the energy consumption simultaneously. In addition, this system will help to solve several problems such as the imbalance of delay and hotspot problems. The effort in this study is focused on the feasibility of using the proposed methodology in different applications. More ongoing experimental work will aim to provide a detailed study for advanced applications, e.g. transport systems for civil purposes.

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Quality of Service in Wireless Sensor Networks: A Survey and Related Patents

Cited by 14 publications

References 36 publications

Software‐defined dynamic QoS provisioning for smart metering in energy Internet using fog computing and network calculus

Software‐defined dynamic QoS provisioning for smart metering in energy Internet using fog computing and network calculus

Collaborative body sensor networks: Taxonomy and open challenges

Use of multiple mobile sinks in wireless sensor networks for large‐scale areas

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